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Pipeline Excellence Director Jobs

2,509 active opportunities · Updated for October 2026

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Explore current pipeline excellence director jobs. Use filters to narrow by work mode, employment type, experience and date posted.

D
Datadog
📍 New York• Full-time• From $156K/yr
1mo ago

The Team We are Datadog’s in-house product experts. The Technical Solutions team enables Datadog’s worldwide growth by educating potential partners and ensuring that our integration ecosystem is high-performing, secure, and valuable. Partner Technology Solutions Engineers (TSEs) are the technical bridge between Datadog and our third-party developer community. We act as consultants, helping partners build world-class monitoring solutions on the Integration Developer Platform (IDP) . The Opportunity Datadog is looking for a Partner Technology Solutions Engineer to join our fast-paced team. You will be the primary technical contact for our partners, guiding them through the entire integration lifecycle—from initial architectural design to final publication on the Datadog Marketplace. This is a unique role that combines deep technical troubleshooting with high-level consulting and platform advocacy. You will work directly with external developers and see your contributions immediately reflected in the Datadog ecosystem. You Will Act as the technical lead for partners, advising on OAuth flows, log pipelines, OpenTelemetry, and agent-based vs. API-based configurations Perform architectural assessments and deep-dive code reviews for partner integrations in the integrations-extras and marketplace repositories, ensuring they meet our Quality Rubric Solve complex technical challenges for partners via Zendesk, Slack, and dedicated technical consultations Identify friction points in our Integration Developer Platform (IDP) and partner with our internal Product and Engineering teams to build a better developer experience Maintain public-facing developer documentation and internal tracking systems ( JIRA ) to ensure transparency and scale You Are A technical expert with 3+ years of experience in a technical role (Support Engineering, Solutions Architecture, or Software Development) Proficient in at least one language (Python or Go preferred) An observability enthusiast who unders

pythonlinuxai
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We’re looking for an Engineering Manager to lead our Sensitive Data Scanner (SDS) Telemetry team. The SDS group’s mission is to be the world’s easiest-to-use tool to discover, classify, manage, and report sensitive data risks across cloud, on-premise, and code environments. This team builds and scales the detection capabilities that scan all telemetry data flowing into Datadog — logs, APM spans, and RUM events — operating in streaming, at processing time, and at very large scale. You’ll lead a small, close-knit team based in Paris, with the opportunity to shape how the team grows as SDS Telemetry’s scope expands. It’s a chance to combine hands-on technical leadership with direct customer and product impact in the security and observability space. At Datadog, we place value in our office culture — the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Lead and grow a team of engineers building real-time sensitive data detection across Datadog’s Logs, APM, and RUM telemetry pipelines Partner closely with the Logs, APM, and RUM teams, plus Datadog’s Trust & Safety team, to align on roadmap and integration priorities Shape product direction by working closely with Product, grounding decisions in customer needs and business impact Stay hands-on: contribute to design decisions and participate in the team’s on-call rotation Recruit, mentor, and develop engineers as the team grows beyond its initial size Help build a strong engineering culture as part of Datadog’s broader Sensitive Data Scanner group Who You Are: You have experience building and shipping revenue-generating products, with strong product acumen and a customer-first mindset You have hands-on experience with Go and/or Java, and a track record building distributed, streaming systems at scale You have experience managing engineers — or are

javaaigo
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D
Datadog
📍 France• Full-time
1mo ago

The Applied AI team designs and builds algorithmically driven features in the Datadog app. We work across a range of applications, primarily focusing on analysis on streaming data such as anomaly detection , error outliers and faulty deployment analysis . As an Applied Scientist you will work on building models and algorithms for machine learning powered features within the Datadog platform. You will work closely with our engineering and product partners to explore, build, scale and deliver these features that we incubate within the Applied AI team. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Design solutions for our different use cases. You will research and benchmark relevant algorithms to find the best fit for our use-cases Leverage machine learning algorithms and statistical techniques to build new scalable product features Develop, deploy and monitor new and existing features to production Participate in our journal club by reading and presenting the latest academic research papers to the team Explore, analyze and tell the story behind high volumes of data flowing through Datadog systems Maintain and monitor the models, services and infrastructure owned by your team Participate in your team’s on-call rotation Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering, Machine Learning or related scientific field or equivalent experience You have experience working with high-scale systems and datasets including building models, applying machine learning to real business problems, and writing production data pipelines You can explain complex ideas and algorithms to non-technical audiences You care about code simplicity and performance You are excited to work on

machine learningaigo
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D
Datadog
📍 USA, Remote• Full-time• Remote• From $118K/yr
1mo ago

Datadog is seeking a motivated and experienced Security Sales Engineer to join our dynamic enterprise sales engineering team. In this role, you will play a critical part in driving our security sales efforts by providing technical expertise and delivering compelling solutions to our customers. You will work closely with our enterprise sales engineers and sales team to identify customer needs, craft go to market strategy, demonstrate the value of Datadog's security solutions, and ensure customer satisfaction. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What you will do: Support the Enterprise Security Sales team in driving adoption of Datadog’s security offering within target strategic accounts. Collaborate with the broader sales team to identify and understand security requirements across Datadog’s Enterprise customer base. Conduct detailed product demonstrations and presentations, showcasing the capabilities and benefits of Datadog's security solutions. Provide technical expertise and support throughout the sales cycle, including during customer evaluations and proof-of-value initiatives. Develop and maintain a deep understanding of Datadog's security products, industry trends and current vulnerabilities, staying updated with the latest features and enhancements. Assist in the creation of technical proposals, documentation, and other sales materials. Work closely with the product management and engineering teams to relay customer feedback and influence product development. Participate in industry events, conferences, and webinars to promote Datadog's security solutions.. Who You Are : Bachelor’s degree in Computer Science, Information Technology, or a related field. Deep experience with SIEM platforms and detection pipelines, SOC workflows (alert triage

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As a Research Engineer on our team, you will partner with Research Scientists to turn research ideas into working systems, building the data, tooling, and infrastructure that enable rapid iteration, trustworthy evaluation, and a smooth path from prototype to production. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Build and operate multimodal data pipelines, training and evaluation infrastructure, benchmarks, and internal tooling Implement models, run experiments at scale, and profile for reliability, performance, and cost Build simulation environments and replay infrastructure for agent training and evaluation Orchestrate distributed training and distributed RL with Ray, including scheduling, scaling, and failure recovery Establish rigorous automated benchmarks and regression tests for world model predictions, agent performance, and simulation fidelity Collaborate with Research Scientists, Product, and Engineeri

pythongitai
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Role Overview Own the end-to-end technology strategy and roadmap for the Partner, Customer success, Professional Services and Customer Support organizations, translating business objectives into scalable, AI-native platforms. Lead a small team of Product Managers while staying hands-on across solutioning, architecture, and delivery. We are looking to speak to candidates who are based in Palo Alto for our hybrid working model. Key Responsibilities Partner Technology Own the Partner Center technology roadmap spanning cloud provider integrations, partner attribution & telemetry, and incentive/MDF management Drive build-vs-buy decisions for the Partner platform in direct partnership with Partner leadership Deliver solutions that support the full partner lifecycle: onboarding, co-sell, information sharing, support, progress tracking, and program management across Resellers, Technology Partners, ISVs, and Cloud Marketplaces Align partner technology with Sales, Partner Ops, and Partner Specialist workflows Customer Success Technology Own the Customer Success technology stack supporting CSMs across the full customer lifecycle: onboarding, adoption, expansion, and renewal Partner with Customer Success leadership to translate business objectives into scalable tooling and automation Enable CSM productivity through health score visibility, account intelligence, and proactive risk alerting Ensure tight integration between Customer Success platforms and Sales, Support, Billing, and Product systems Drive adoption of AI-assisted workflows for CSMs including next-best-action recommendations, sentiment signals, and churn risk indicators Customer Support Technology Own the Customer Support technology stack to enable customer support team with right tooling, including AI/agentic infrastructure, ETL/data pipelines, Workforce Management, and customer engagement tooling (chat, voice, workflow automation) Partner with Technical Support, Customer Success, and Professional Services to al

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Mongodb
📍 Gurugram• Full-time
1mo ago

We’re looking for a Software Engineer 3 to join our Marketing Technology Engineering team within Marketing Operations - Technology & Automation. This is a hands-on engineering role for someone who enjoys building reliable, scalable digital platforms and internal systems that improve how teams ship, measure, and optimize web experiences. You’ll work across application development, integrations, experimentation, data-informed decision making, and AI-enabled workflows that help the team move faster and deliver better outcomes. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. What you’ll do Build and maintain production-quality software that powers martech experiences Design and implement backend services, internal tools, automations, and integrations across the martech ecosystem Improve system reliability, observability, maintainability, and developer experience across the team’s platforms Contribute to experimentation, personalization, and data workflows that support better customer and developer experiences Help evaluate and apply AI-enabled capabilities and tools where they can improve engineering velocity, quality, or user experience Participate in code reviews, technical design discussions, and team planning Take ownership of projects from implementation through rollout, monitoring, and iteration What we’re looking for 3+ years of professional software engineering experience building and supporting production systems Strong coding skills in one or more modern programming languages such as JavaScript or Python Experience building web applications, backend services, APIs, data pipelines, or internal platforms Solid understanding of software engineering fundamentals including testing, debugging, code quality, and maintainability Experience working with cloud services, CI/CD workflows, and modern development practices Ability to work across systems and collaborate effectively with cross-functional partners Strong writte

javascriptpythonjava
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M
Mongodb
📍 United States• Full-time• From $126K/yr
1mo ago

Senior Forward Deployed Engineers (FDE) sit at the intersection of enterprise customer environments and a fast-moving internal product. They partner directly with customers to design, build, troubleshoot, and improve production solutions, and they are ultimately accountable for helping customers get to production. This role is best suited for engineers who want to own technical outcomes end to end: understanding what a customer is trying to build, shipping the integration, and feeding learnings back into the product roadmap. This role will be based remotely in the United States (East Coast). Responsibilities Customer success Serve as the primary technical owner for customer engagements from initial discovery through production rollout Understand each customer's architecture, constraints, and definition of success, and drive toward that outcome Manage expectations, communicate risks clearly, and help customers navigate technical decisions with confidence Technical integration Build the connectors, pipelines, and supporting tooling needed to make the platform work inside real enterprise environments Write production-quality code, troubleshoot issues, and implement fixes directly in active workstreams Work effectively within customer environments that have different stacks, infrastructure, and integration constraints Product feedback loop Capture product feedback with precision, including logs, reproduction steps, and a clear proposed path forward Use customer engagements to identify product gaps, surface recurring patterns, and help improve the product roadmap Document technical decisions and tradeoffs clearly so product and engineering teams can extend the work Workstream collaboration Partner closely with product and engineering teams to help turn field patterns into reusable product capabilities Contribute directly in focused workstreams by helping drive technical design, implementation, and delivery Make sound engine

mongodbawsazure
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M
Mongodb
📍 United States• Full-time• From $151K/yr
1mo ago

We’re looking for a Senior Engineering Manager who is ready to lead through ambiguity and improve how software gets built at MongoDB. This role leads teams focused on developer productivity, with an emphasis on measurable improvements to the software development lifecycle. This role can be based remotely in the United States. The Team The AXIS team (AI, X-functional tools, Insights, and Signals) sits within Developer Productivity and is responsible for overseeing the metrics and observability infrastructure of our expansive developer environment to help build a strong data-driven culture. You’ll also be a key partner in building the agentic ecosystem for AI-driven development across engineering. Candidate Profile We’re looking for an experienced leader with a passion for solving the big challenge of measuring developer productivity and providing the actionable signals that help teams improve their performance. They should be comfortable working collaboratively with other leaders and partners across our Engineering and Data teams in maximizing the use of data for insights and AI enablement. The right candidate for this role will have 4+ years of experience managing software engineers, including hiring, performance management, growth planning, and compensation; required for external candidates and preferred for internal candidates 8+ years of hands-on software engineering experience building and operating production systems; experience in developer tooling, platform engineering, observability, or data engineering is a strong plus Demonstrated the ability to lead through ambiguity, work across team boundaries, and deliver outcomes without close supervision Strong customer orientation and sound judgment in finding practical, high-leverage solutions Experience working with systems involving analytics, data pipelines, and metrics platforms Experience with AI tools development and enablement efforts Strong technical judgment, including the ability to evaluate t

mongodbawsazure
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M
Mongodb
📍 Austin; New York City; San Francisco; Seattle; United States• Full-time• From $127K/yr
1mo ago

We are hiring an experienced Security Software Engineer (Staff or Senior) for our Infrastructure Security team to design and build scalable security controls and services within MongoDB Atlas multi-cloud infrastructure. The team sits within the Site Reliability Engineering organization and works with other engineering teams to ensure that our infrastructure adheres to the highest security standards. This role can be based out of our New York City, Austin, Seattle or San Francisco offices, or work fully remotely on standard East Coast business hours. Responsibilities: Design and build core security primitives and services that protect MongoDB Atlas compute, networking, and identity across AWS, Azure, and GCP Build secure-by-default infrastructure using Linux security mechanisms (AppArmor, SELinux, seccomp, cgroups), Kubernetes, and eBPF to enforce runtime policies and gain deep visibility into systems behaviour Develop APIs, automation, and tooling that manage security posture at scale (CSPM, vulnerability management, workload identity) and provide monitoring, logging, and alerting pipelines that integrate with our tooling (Grafana, Splunk, Victoria Metrics.) Integrate security into our CI/CD and infrastructure-as-code workflows (Terraform) so that security controls are versioned, reviewed, and deployed just like any other code Lead complex projects end‑to‑end, from problem discovery and design docs to implementation, rollout, and long‑term ownership Collaborate with SRE, platform and product engineering teams to define secure architectures for new infrastructure and services Qualifications: You might be a great fit if you match some of the following: 5+ years of experience in Software Engineering, Site Reliability Engineering, or similar roles, preferably with relevant security work Proficiency with at least one programming language (Java, Golang, Rust, Python, or C/C++) and experience with infrastructure-as-code tools (Terraform) to automate security configurations

pythonjavamongodb
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M
Mongodb
📍 Alberta• Full-time• From C$191K/yr
1mo ago

We’re looking for a Senior Engineering Manager who is ready to lead through ambiguity and improve how software gets built at MongoDB. This role leads teams focused on developer productivity, with an emphasis on measurable improvements to the software development lifecycle. This role can be based remotely in Canada. The Team The AXIS team (AI, X-functional tools, Insights, and Signals) sits within Developer Productivity and is responsible for overseeing the metrics and observability infrastructure of our expansive developer environment to help build a strong data-driven culture. You’ll also be a key partner in building the agentic ecosystem for AI-driven development across engineering. Candidate Profile We’re looking for an experienced leader with a passion for solving the big challenge of measuring developer productivity and providing the actionable signals that help teams improve their performance. They should be comfortable working collaboratively with other leaders and partners across our Engineering and Data teams in maximizing the use of data for insights and AI enablement. The right candidate for this role will have 4+ years of experience managing software engineers, including hiring, performance management, growth planning, and compensation; required for external candidates and preferred for internal candidates 8+ years of hands-on software engineering experience building and operating production systems; experience in developer tooling, platform engineering, observability, or data engineering is a strong plus Demonstrated the ability to lead through ambiguity, work across team boundaries, and deliver outcomes without close supervision Strong customer orientation and sound judgment in finding practical, high-leverage solutions Experience working with systems involving analytics, data pipelines, and metrics platforms Experience with AI tools development and enablement efforts Strong technical judgment, including the ability to evaluate tradeoffs, i

mongodbawsazure
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M
Mongodb
📍 Gurugram• Full-time
1mo ago

Senior Forward Deployed Engineers (FDE) sit at the intersection of enterprise customer environments and a fast-moving internal product. They partner directly with customers to design, build, troubleshoot, and improve production solutions, and they are ultimately accountable for helping customers get to production. This role is best suited for engineers who want to own technical outcomes end to end: understanding what a customer is trying to build, shipping the integration, and feeding learnings back into the product roadmap. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Responsibilities Customer success Serve as the primary technical owner for customer engagements from initial discovery through production rollout Understand each customer's architecture, constraints, and definition of success, and drive toward that outcome Manage expectations, communicate risks clearly, and help customers navigate technical decisions with confidence Technical integration Build the connectors, pipelines, and supporting tooling needed to make the platform work inside real enterprise environments Write production-quality code, troubleshoot issues, and implement fixes directly in active workstreams Work effectively within customer environments that have different stacks, infrastructure, and integration constraints Product feedback loop Capture product feedback with precision, including logs, reproduction steps, and a clear proposed path forward Use customer engagements to identify product gaps, surface recurring patterns, and help improve the product roadmap Document technical decisions and tradeoffs clearly so product and engineering teams can extend the work Workstream collaboration Partner closely with product and engineering teams to help turn field patterns into reusable product capabilities Contribute directly in focused workstreams by helping drive technical design, implementation, and delivery Make sound engineering decisions under

mongodbawsazure
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We are hiring an experienced Security Software Engineer (Staff or Senior) for our Infrastructure Security team to design and build scalable security controls and services within MongoDB Atlas multi-cloud infrastructure. The team sits within the Site Reliability Engineering organization and works with other engineering teams to ensure that our infrastructure adheres to the highest security standards. This role can be based out of our Dublin office, or work fully remotely in Ireland. Responsibilities: Design and build core security primitives and services that protect MongoDB Atlas compute, networking, and identity across AWS, Azure, and GCP Build secure-by-default infrastructure using Linux security mechanisms (AppArmor, SELinux, seccomp, cgroups), Kubernetes, and eBPF to enforce runtime policies and gain deep visibility into systems behaviour Develop APIs, automation, and tooling that manage security posture at scale (CSPM, vulnerability management, workload identity) and provide monitoring, logging, and alerting pipelines that integrate with our tooling (Grafana, Splunk, Victoria Metrics.) Integrate security into our CI/CD and infrastructure-as-code workflows (Terraform) so that security controls are versioned, reviewed, and deployed just like any other code Lead complex projects end‑to‑end, from problem discovery and design docs to implementation, rollout, and long‑term ownership Collaborate with SRE, platform and product engineering teams to define secure architectures for new infrastructure and services Qualifications: You might be a great fit if you match some of the following: 5+ years of experience in Software Engineering, Site Reliability Engineering, or similar roles, preferably with relevant security work Proficiency with at least one programming language (Java, Golang, Rust, Python, or C/C++) and experience with infrastructure-as-code tools (Terraform) to automate security configurations and processes A deep understanding of Linux and networking concepts,

pythonjavamongodb
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P
Pinterest
📍 United States• Full-time• Remote• From $177.2K/yr
1mo ago

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Pinterest's performance marketing engineering team owns the end-to-end systems that turn marketing dollars into measured user growth spanning attribution, bidding, budget optimization, and campaign management across major advertising platforms. This role is responsible for designing systems that scale across channels and adapt as privacy landscapes shift. What you’ll do: Lead the technical roadmap for the performance marketing platform, defining the highest-impact investments across attribution, bidding, budget optimization, and campaign management Drive hands-on engineering across ad platform integrations, event pipelines, and production systems that deploy and measure marketing spend Design and evolve the measurement stack — attribution models, conversion signal collection, incrementality methodology, and privacy-resilient approac

REMOTEpythonjavasql
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P
Pinterest
📍 United States• Full-time• Remote• From $132.4K/yr
1mo ago

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Are you passionate about building impactful products for sales and finance teams? Come join the IT Enterprise Systems team at Pinterest where you will be responsible for advancing our sales and marketing systems. What you’ll do: Design, build, and operate full‑stack applications and services on Pinterest’s enterprise infrastructure to support our Sales, Marketing, and Finance teams, from backend services and APIs through integrations and user‑facing workflows. Lead the technical design and implementation of GenAI/ML‑powered services and pipelines that automate and augment enterprise workflows (for example, summarizing sales interactions, enriching account data, or surfacing intelligent recommendations), including clear evaluation frameworks, observability, and validation guardrails. Own the end‑to‑end software development lifecycle for th

REMOTEjavascriptpythonjava
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